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A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications.

ABSTRACT: The problem of the genetics of related phenotypes is often addressed by analyzing adjusted-model traits, but such traits warrant cautious interpretation. Here, we adopt a joint view of adiposity traits in ~322,154 subjects (GIANT consortium). We classify 159 signals associated with body mass index (BMI), waist-to-hip ratio (WHR), or WHR adjusted for BMI (WHRadjBMI) at P < 5 × 10-8, into four classes based on the direction of their effects on BMI and WHR. Our classes help differentiate adiposity genetics with respect to anthropometry, fat depots, and metabolic health. Class-specific Mendelian randomization reveals that variants associated with both WHR-decrease and BMI increase are linked to metabolically rather favorable adiposity through beneficial hip fat. Class-specific enrichment analyses implicate digestive systems as a pathway in adiposity genetics. Our results demonstrate that WHRadjBMI variants capture relevant effects of "unexpected fat distribution given the BMI" and that a joint view of the genetics underlying related phenotypes can inform on important biology.

SUBMITTER: Winkler TW

PROVIDER: S-EPMC5956079 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications.

Winkler Thomas W TW Günther Felix F Höllerer Simon S Zimmermann Martina M Loos Ruth Jf RJ Kutalik Zoltán Z Heid Iris M IM

Nature communications 20180516 1

The problem of the genetics of related phenotypes is often addressed by analyzing adjusted-model traits, but such traits warrant cautious interpretation. Here, we adopt a joint view of adiposity traits in ~322,154 subjects (GIANT consortium). We classify 159 signals associated with body mass index (BMI), waist-to-hip ratio (WHR), or WHR adjusted for BMI (WHRadjBMI) at P < 5 × 10<sup>-8</sup>, into four classes based on the direction of their effects on BMI and WHR. Our classes help differentiate ...[more]

PMID: 29769528

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Project description:BackgroundThe effects of air pollutants, particularly polycyclic aromatic hydrocarbons (PAHs), on the skin microbiome remain poorly understood. Thus, to better understand the interplay between air pollutants, microbiomes, and skin conditions, we applied metagenomics and metabolomics to analyze the effects of PAHs in air pollution on the skin microbiomes of over 120 subjects residing in two cities in China with different levels of air pollution.ResultsThe skin microbiomes differentiated into two cutotypes (termed 1 and 2) with distinct taxonomic, functional, resistome, and metabolite compositions as well as skin phenotypes that transcended geography and host factors. High PAH exposure was linked to dry skin and cutotype 2, which was enriched with species with potential biodegradation functions and had reduced correlation network structure integrity. The positive correlations identified between dominant taxa, key functional genes, and metabolites in the arginine biosynthesis pathway in cutotype 1 suggest that arginine from bacteria contributes to the synthesis of filaggrin-derived natural moisturizing factors (NMFs), which provide hydration for the skin, and could explain the normal skin phenotype observed. In contrast, no correlation with the arginine biosynthesis pathway was observed in cutotype 2, which indicates the limited hydration functions of NMFs and explains the observed dry skin phenotype. In addition to dryness, skin associated with cutotype 2 appeared prone to other adverse conditions such as inflammation.ConclusionsThis study revealed the roles of PAHs in driving skin microbiome differentiation into cutotypes that vary extensively in taxonomy and metabolic functions and may subsequently lead to variations in skin-microbe interactions that affect host skin health. An improved understanding of the roles of microbiomes on skin exposed to air pollutants can aid the development of strategies that harness microbes to prevent undesirable skin conditions. Video Abstract.

Dataset Information

A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications.

Publications

A joint view on genetic variants for adiposity differentiates subtypes with distinct metabolic implications.

Similar Datasets

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